GGPLOT2: Us in a Nutshell

## 'data.frame':    248 obs. of  5 variables:
##  $ country  : chr  "US" "US" "US" "US" ...
##  $ date     : Date, format: "2020-09-25" "2020-09-24" ...
##  $ confirmed: num  7032712 6977658 6933548 6896218 6856884 ...
##  $ deaths   : num  203750 202798 201884 200786 199865 ...
##  $ recovered: num  2727335 2710183 2670256 2646959 2615949 ...

GGPLOt2 Plots of Cumulative Cases and Deaths

Source: New York Times

cumm_deaths <-ggplot(df) +geom_line(aes(x=date,y=deaths),lwd=3,col="blue") + 
    scale_x_date(date_breaks = "1 month") +
  scale_y_continuous(labels = comma) +
   theme(axis.text.x=element_text(angle =- 45, vjust = 0.5)) +
  labs(title="US Cumulative Total Deaths",x="Date Reported",y="Cumulative Deaths")
ggplotly(cumm_cases)

ggplotly(cumm_deaths)

GGPLOt2 Plots of Daily Deaths and Cases

Source: European CDPC

Average US Covid-19 Deaths/day

mean(df1death$Deaths)

## [1] 965.7536

NPR/Washington Uni 300,000 by Dec. 1,2020

(300000 - sum(df1death$Deaths))/65

## [1] 1480.4

Washington Uni and Yahoo/USA Today:

410,000 Jan. 1 2021

(410000 - sum(df1death$Deaths)) / 97 # Jan 1, 2021

## [1] 2126.041

Average Deaths/Day for Jan. 31, 2020

410,000

(410000 - sum(df1death$Deaths))/ 127 # Jan 31, 2020

## [1] 1623.827

Histograms of Daily Cases and Deaths

ggplot(df1) + geom_bar(aes(x=Deaths,fill=..count..),stat="bin")

ggplot(df1) + geom_bar(aes(x=Cases,fill=..count..),stat="bin")